Source: drugtargetreview.com Researchers have designed a novel approach to use deep learning to improve their understanding of how proteins interact in the body. According to the team, their findings could result in more accurate structure models of protein interactions in various diseases and better drug designs that target protein interactions. The study, conducted at Purdue Read More

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Source: analyticsinsight.net Machine learning has become omnipresent today with applications extending from precise diagnosis of skin diseases and cardiac arrhythmia to recommendations on streaming channels and gaming. However, in the distributed machine learning scheme, imagine a scenario where one ‘laborer’ or ‘peer’ is undermined. In what capacity can the aggregation framework be strong to the Read More

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Source: physicsworld.com What is the actual structure of graphene oxide nanoflakes? This question is important for optimizing the properties of the carbon material in real-world applications, and researchers at CSIRO in Australia have now tried to answer it using machine learning. Their approach uses over 20,000 possible structure candidates to find truly representative models and is Read More

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Source: healthitanalytics.com December 24, 2019 – Researchers at Purdue University have created a new framework for mining data to train machine learning models used in drug development. Using machine learning for drug development requires researchers to create a process for the computer to extract needed information from a pool of data points. Drug scientists have to pull biological data and train Read More

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Source: novinite.com Scientists at the University of Colorado at boulder (USA), predict a catastrophic decline in human intelligence due to the increased carbon dioxide content in the atmosphere, according to the website Phys.org. Researchers tracked how increased levels of carbon dioxide affect children’s learning. Previous experiments have shown that high concentrations of gas actually affect their mental Read More

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Source: indiaeducationdiary.in New Delhi: The 3rd International Conference on Machine Learning and Data Science (ICMLDS 2019) technically co-sponsored by ACM Digital Library was held at Mahindra Ecole Centrale (MEC), Hyderabad. The two-day conference(held on 16th & 17th of December 2019) focused on topics that are of interest to computer and computational scientists and engineers. ICMLDS-2019 brought Read More

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Source: phys.org Researchers at the EMBL’s European Bioinformatics Institute (EMBL-EBI) have created the largest reference phosphoproteome to date of almost 120,000 human phosphosites. To identify those most likely to be critical, they used a machine learning approach capable of ranking them according to functional importance. Proteins are the core molecular machines of the cell that can be Read More

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Source: technologynetworks.com Deep learning, a type of artificial intelligence, can boost the power of MRI in predicting attention deficit hyperactivity disorder (ADHD), according to a study published in Radiology: Artificial Intelligence. Researchers said the approach could also have applications for other neurological conditions. The human brain is a complex set of networks. Advances in functional Read More

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Source: itproportal.com You see them all over city streets: pedestrians wearing headphones or earbuds – their faces glued to their phones as they stroll along oblivious to their surroundings. Known as “twalking,” the behavior is not without its dangers. Headphone-wearing pedestrians often can’t hear the auditory cues – horns, shouts, or the sound of approaching Read More

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Source: phys.org In a world-first, a team of Griffith University researchers has used an artificial intelligence method to better predict RNA secondary structures, with the hope it can be developed into a tool to better understand how RNAs are implicated in various diseases such as cancer. In all forms of life, ribonucleic acid (RNA) is Read More

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Source: healthimaging.com Utilizing a deep learning algorithm could help radiologists determine valuable coronary artery calcium scores (CACS) in a fraction of the time. Such scores have proven to be more predictive of cardiovascular risk than any other biomarker, but quantifying CACS via imaging remains a time-consuming and labor-intensive task, wrote authors of a new study published Nov. Read More

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Source: healthcareitnews.com Artificial intelligence technology based on a deep learning model could help cardiologists predict irregular heart rhythms, known as atrial fibrillation, before it develops. WHY IT MATTERSThat’s the conclusion drawn from two studies to be presented at the American Heart Association Scientific Sessions 2019 and conducted by Geisinger researchers. A team of scientists trained Read More

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Source: phys.org A UCLA research team has devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. The researchers use artificial intelligence to turn two-dimensional images into stacks of virtual three-dimensional slices showing activity inside organisms. Read More

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Source: genengnews.com Researchers at the Sanford Burnham Prebys Medical Discovery Institute say that machine learning’s powerful ability to detect patterns in complex data is revolutionizing how scientists diagnose disease and, now, how they discover new drugs. The Sanford Burnham team has developed a machine-learning algorithm that gleans information from microscope images that allow for high-throughput Read More

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Source: venturebeat.com What’s the best way to measure the quality of media generated from whole cloth by AI models? It’s not easy. One of the most popular metrics for images is the Fréchet Inception Distance (FID), which takes photos from both the target distribution and the model being evaluated and uses an AI object recognition system to capture important Read More

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Source: indiatoday.in Researchers of the Indian Institute of Technology Hyderabad have developed low power chips that can be used in Artificial Intelligence-powered devices. They have developed Magnetic quantum-dot cellular automata (MQCA) based on nanomagnetic logic architectural design methodology of approximate arithmetic circuits. The researchers are working towards a vision of realizing resource-constrained Magnetic Chips for Read More

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Source: techxplore.com Deep learning can help scholars restore ancient Greek texts. Specifically, researchers at University of Oxford (Thea Sommerschield and Professor Jonathan Prag) and DeepMind (Yannis Assael) built Pythia, training a neural network to guess missing words or characters from Greek inscriptions. These were on surfaces including stone, ceramic and metal. They were between 1500 Read More

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Source: news18.com Designers of machine translation tools still mostly rely on dictionaries to make a foreign language understandable. But now there is a new way: numbers. Facebook researchers say rendering words into figures and exploiting mathematical similarities between languages is a promising avenue, even if a universal communicator a la Star Trek remains a distant Read More

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Source: phys.org A trio of researchers from Chonnam National University, Nanjing University of Information Science and Technology and the Chinese Academy of Sciences has found that a deep learning convolutional neural network was able to accurately predict El Niño events up to 18 months in advance. In their paper published in the journal Nature, Yoo-Geun Ham, Read More

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source: news.mit.edu A novel system developed by MIT researchers automatically “learns” how to schedule data-processing operations across thousands of servers — a task traditionally reserved for imprecise, human-designed algorithms. Doing so could help today’s power-hungry data centers run far more efficiently. Data centers can contain tens of thousands of servers, which constantly run data-processing tasks Read More

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Source: machinedesign.com Artificial Intelligence (AI) gets plenty of attention these days, but one researcher at the U.S. Naval Research Laboratory believes one particular AI technique might be getting a little too much. “People have focused on an area of machine learning—deep learning (aka deep networks) — and less so on the variety of other artificial Read More

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Source:techxplore.com Since its invention by a Hungarian architect in 1974, the Rubik’s Cube has furrowed the brows of many who have tried to solve it, but the 3-D logic puzzle is no match for an artificial intelligence system created by researchers at the University of California, Irvine. DeepCubeA, a deep reinforcement learning algorithm programmed by Read More

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Artificial Intelligence